Entwicklung innovativer satellitengestützter Methoden zur verbesserten PV-Ertragsvorhersage auf verschiedenen Zeitskalen für Anwendungen auf Verteilnetzebene

Meilinger, Stefanie; Herman-Czezuch, Anna; Kimiaie, Nicola; Schirrmeister, Christopher; Yousif, Rone; Geiß, Stefan; Scheck, Leonhard; Weißmann, Martin; Gödde, Felix; Mayer, Bernd; Zinner, Tobias; Barry, James; Pfeilsticker, Klaus; Kraiczy, Markus; Winter, Kevin; Altayara, Abdullah; Rivera, Mariella; Deneke, Hartwig; Witthuhn, Jonas; Betcke, Jethro; Schroedter-Homscheidt, Marion; Hofbauer, Philipp; Rindt, Bernhard

doi:10.18418/opus-5955

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“…Detailed 3D radiative transfer simulations were carried out and the most important factors turn out to be simply the sensor and sun geometry as well as the cloud fraction, which reflects the fact that a pyranometer or PV system sees the entire sky. A detailed description of the MYSTIC LUT is given in Chapter 9, Section 9.1.5 of Meilinger et al (2021).…”

Section: From Tilted To Horizontal Irradiance With Mystic Lookup Tablementioning

confidence: 99%

“…The goal of this work is to demonstrate that PV systems can indeed be used as ground-based sensors for both GHI as well as to infer the optical properties of the atmosphere, in particular the COD. First results are presented from two measurement campaigns carried out in autumn 2018 and summer 2019 in the Allgäu region in southern Germany, as part of the BMWifunded project MetPVNet (Meilinger et al, 2021). In Section 2 the forward model and its calibration are discussed, and the inversion methods are outlined in detail.…”

Section: Introductionmentioning

confidence: 99%

“…Model calibration and inversion was performed with PV power data recorded over two measurement campaigns in autumn 2018 and summer 2019, as part of the MetPVNet measurement campaign [see Chapter 3 ofMeilinger et al (2021)]. There were a total of 24 stations spread out in the region around Kempten (47.715924 • N, 10.314006 • E), as shown in Figure…”

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confidence: 99%

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Irradiance and cloud optical properties from solar photovoltaic systems

Barry

Meilinger

Pfeilsticker

et al. 2023

Preprint

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Abstract. Solar photovoltaic power output is modulated by atmospheric aerosols and clouds and thus contains valuable information on the optical properties of the atmosphere. As a ground-based data source with high spatiotemporal resolution it has great potential to complement other ground-based solar irradiance measurements as well as those of weather models and satellites, thus leading to an improved characterisation of global horizontal irradiance. In this work several algorithms are presented that can retrieve global tilted and horizontal irradiance and atmospheric optical properties from solar photovoltaic data and/or pyranometer measurements. Specifically, the aerosol (cloud) optical depth is inferred during clear sky (completely overcast) conditions. The method is tested on data from two measurement campaigns that took place in Allgäu, Germany in autumn 2018 and summer 2019, and the results are compared with local pyranometer measurements as well as satellite and weather model data. Using power data measured at 1 Hz and averaged to 1 minute resolution, the hourly global horizontal irradiance is extracted with a mean bias error compared to concurrent pyranometer measurements of 11.45 W m−2, averaged over the two campaigns, whereas for the retrieval using coarser 15 minute power data the mean bias error is 16.39 W m−2. During completely overcast periods the cloud optical depth is extracted from photovoltaic power using a lookup table method based on a one-dimensional radiative transfer simulation, and the results are compared to both satellite retrievals as well as data from the COSMO weather model. Potential applications of this approach for extracting cloud optical properties are discussed, as well as certain limitations, such as the representation of 3D radiative effects that occur under broken cloud conditions. In principle this method could provide an unprecedented amount of ground-based data on both irradiance and optical properties of the atmosphere, as long as the required photovoltaic power data are available and are properly pre-screened to remove unwanted artefacts in the signal. Possible solutions to this problem are discussed in the context of future work.

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Section: From Tilted To Horizontal Irradiance With Mystic Lookup Tablementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%